Overview

This book focuses on recent developments in docking simulations for target proteins with chapters on specific techniques or applications for docking simulations, including the major docking programs. Additionally, the volume explores the scoring functions developed for the analysis of docking results and to predict ligand-binding affinity as well as the importance of docking simulations for the initial stages of drug discovery. Written for the highly successful Methods in Molecular Biology series, this collection presents the kind of detail and key implementation advice to ensure successful results.  Authoritative and practical, Docking Screens for Drug Discovery aims to serve those interested in molecular docking simulation and also in the application of these methodologies for drug discovery.

Full Product Details

Author:   Walter Filgueira de Azevedo Jr.
Publisher:   Humana Press Inc.
Imprint:   Humana Press Inc.
Edition:   1st ed. 2019
Volume:   2053
Weight:   0.801kg
ISBN:  

9781493997510

ISBN 10:   1493997513
Pages:   286
Publication Date:   27 August 2019
Audience:   Professional and scholarly ,  College/higher education ,  Professional & Vocational ,  Postgraduate, Research & Scholarly
Format:   Hardback
Publisher's Status:   Active
Availability:   Manufactured on demand  
We will order this item for you from a manufactured on demand supplier.

Table of Contents

Building Machine-Learning Scoring Functions for Structure-Based Prediction of Intermolecular Binding Affinity.- Integrating Molecular Docking and Molecular Dynamics Simulations.- How Docking Programs Work.- SAnDReS: A Computational Tool for Docking.- Electrostatic Energy in Protein-Ligand Complexes.- Van der Waals Potential in Protein Complexes.- Hydrogen-Bonds in Protein-Ligand Complexes.- Molecular Dynamics Simulations with NAMD2.- Docking with AutoDock4.- Molegro Virtual Docker for Docking.- Docking with GemDock.- Docking with SwissDock.- Molecular Docking Simulations with ArgusLab.- Web Services for Molecular Docking Simulations.- Homology Modeling of Protein Targets with MODELLER.- Machine Learning to Predict Binding Affinity.- Exploring the Scoring Function Space.

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